Establish common business context and semantics so data can be effectively used by applications, ML models, GenAI and AI agents.
Develop and productionise ML solutions for prediction, forecasting, risk, anomaly detection, recommendations and optimisation
Build production-grade GenAI/LLM solutions using approaches such as RAG, embeddings, vector search and tool calling.
Build agentic AI solutions that can reason over trusted data, use tools and APIs, provide recommendations and take actions.
Design appropriate guardrails, access controls, monitoring and human oversight for AI and agentic solutions.
Build reusable APIs, services and workflows that connect data, applications and AI capabilities.
Use platforms such as Pipedream or similar workflow tools where they add value.
Make architecture and technology decisions considering scalability, reliability, security, performance and cost.
Establish strong engineering practices including testing, CI/CD and observability.
Contribute to architecture reviews, technical design and code reviews. • Mentor engineers and help establish engineering and architecture standards
About You
We are looking for someone with strong engineering, data and AI fundamentals who can build production-ready systems.
You should have
4+ years of experience in software engineering, data engineering, AI/ML engineering or a related field.
Experience designing and building scalable, distributed and data-intensive systems.
Experience contributing to or owning architecture and technical design for data or AI platforms.
Strong programming skills in Java and Python. Experience with Scala, Kotlin or similar languages is a plus.
Strong understanding of data architecture, data modelling, distributed systems and data processing.
Experience building data pipelines, data products or data platforms at scale. • Experience with technologies such as Kafka, Spark, Databricks, Flink or equivalent.
Experience with relational and/or NoSQL databases
Good understanding of data quality, governance, metadata, lineage and observability.
Hands-on experience taking ML models from development to production, including deployment, monitoring and evaluation.
Experience with GenAI/LLMs and building practical, production-ready applications.
Understanding of RAG, embeddings, vector search, tool calling and LLM evaluation.
Experience or strong exposure to AI agents and agentic workflows.
Understanding of AI security, guardrails, access control and human oversight.
Experience with at least one cloud platform such as Azure, AWS or Google Cloud.
Strong software engineering practices including automated testing, CI/CD and production operations.
Strong communication and problem-solving skills. • A platform mindset — focused on building reusable capabilities rather than oneoff solutions.
Good to Have
Experience in logistics, shipping, transportation or supply chain.
Experience with real-time and event-driven architectures.
Experience with MLOps and model monitoring.
Experience with production RAG, AI agents or agent orchestration.
Experience with MCP or similar agent/tool integration patterns.
Experience with knowledge graphs, semantic models or entity resolution.
Experience with Pipedream or similar workflow/integration platforms.
Experience with Docker, Kubernetes and cloud-native architectures.
Experience leading technical design or architecture for large-scale platforms.
Why This Role
This is a greenfield opportunity to help build the foundation for the next generation of supply-chain intelligence at Maersk. Our vision is: Data Foundation → Data Products & Context → ML & Intelligence → Recommendations → GenAI → Agentic AI The data foundation is the core layer, providing trusted, reusable and contextualised data to products, ML models, GenAI applications and AI agents.
The goal is to build a platform where new data and AI capabilities can be developed faster, reused across multiple use cases and scaled across the supply chain without repeatedly rebuilding the underlying foundation. You will help shape the architecture, data foundation, engineering practices and AI capabilities that will enable future digital supply-chain experiences at Maersk.
Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.
We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.
